These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

35 related articles for article (PubMed ID: 10877323)

  • 1. BAYESIAN MODELING LONGITUDINAL DYADIC DATA WITH NONIGNORABLE DROPOUT, WITH APPLICATION TO A BREAST CANCER STUDY.
    Zhang G; Yuan Y
    Ann Appl Stat; 2012 Jun; 6(2):753-771. PubMed ID: 23814631
    [TBL] [Abstract][Full Text] [Related]  

  • 2. A dynamic approach for reconstructing missing longitudinal data using the linear increments model.
    Aalen OO; Gunnes N
    Biostatistics; 2010 Jul; 11(3):453-72. PubMed ID: 20388914
    [TBL] [Abstract][Full Text] [Related]  

  • 3. An imputation approach for a time-to-event analysis subject to missing outcomes due to noncoverage in disease registries.
    Shih JH; Albert PS; Fine J; Liu D
    Biostatistics; 2023 Dec; 25(1):117-133. PubMed ID: 36534828
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Discrete Choice Models for Nonmonotone Nonignorable Missing Data: Identification and Inference.
    Tchetgen EJT; Wang L; Sun B
    Stat Sin; 2018 Oct; 28(4):2069-2088. PubMed ID: 33994754
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Bayesian joint modelling of longitudinal data on abstinence, frequency and intensity of drinking in alcoholism trials.
    Buta E; O'Malley SS; Gueorguieva R
    J R Stat Soc Ser A Stat Soc; 2018 Jun; 181(3):869-888. PubMed ID: 31123390
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Bayesian Modeling and Inference for Nonignorably Missing Longitudinal Binary Response Data with Applications to HIV Prevention Trials.
    Wu J; Ibrahim JG; Chen MH; Schifano ED; Fisher JD
    Stat Sin; 2018 Oct; 28():1929-1963. PubMed ID: 30595637
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Estimation of regression models for the mean of repeated outcomes under nonignorable nonmonotone nonresponse.
    Vansteelandt S; Rotnitzky A; Robins J
    Biometrika; 2007 Dec; 94(4):841-860. PubMed ID: 27453583
    [TBL] [Abstract][Full Text] [Related]  

  • 8. A Latent Transition Analysis Model for Latent-State-Dependent Nonignorable Missingness.
    Sterba SK
    Psychometrika; 2016 Jun; 81(2):506-34. PubMed ID: 25697371
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Joint modeling of recurrent event processes and intermittently observed time-varying binary covariate processes.
    Li S
    Lifetime Data Anal; 2016 Jan; 22(1):145-60. PubMed ID: 25573223
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Regression modeling of longitudinal data with outcome-dependent observation times: extensions and comparative evaluation.
    Tan KS; French B; Troxel AB
    Stat Med; 2014 Nov; 33(27):4770-89. PubMed ID: 25052289
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Analysis of Ordinal Outcomes with Longitudinal Covariates Subject to Missingness.
    Goodman MS; Li Y; Stoddard AM; Sorensen G
    J Appl Stat; 2014 Jan; 41(5):1040-1052. PubMed ID: 24791038
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Joint modeling of transitional patterns of Alzheimer's disease.
    Liu W; Zhang B; Zhang Z; Zhou XH
    PLoS One; 2013; 8(9):e75487. PubMed ID: 24073268
    [TBL] [Abstract][Full Text] [Related]  

  • 13. An exploration of fixed and random effects selection for longitudinal binary outcomes in the presence of nonignorable dropout.
    Li N; Daniels MJ; Li G; Elashoff RM
    Biom J; 2013 Jan; 55(1):17-37. PubMed ID: 23124889
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Longitudinal data analysis with non-ignorable missing data.
    Tseng CH; Elashoff R; Li N; Li G
    Stat Methods Med Res; 2016 Feb; 25(1):205-20. PubMed ID: 22637472
    [TBL] [Abstract][Full Text] [Related]  

  • 15. A Bayesian Shrinkage Model for Incomplete Longitudinal Binary Data with Application to the Breast Cancer Prevention Trial.
    Wang C; Daniels MJ; Scharfstein DO; Land S
    J Am Stat Assoc; 2010 Dec; 105(492):1333-1346. PubMed ID: 21516191
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Estimation of average treatment effect with incompletely observed longitudinal data: application to a smoking cessation study.
    Chen HY; Gao S
    Stat Med; 2009 Aug; 28(19):2451-72. PubMed ID: 19462416
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Imputation-based strategies for clinical trial longitudinal data with nonignorable missing values.
    Yang X; Li J; Shoptaw S
    Stat Med; 2008 Jul; 27(15):2826-49. PubMed ID: 18205247
    [TBL] [Abstract][Full Text] [Related]  

  • 18. A transitional model for longitudinal binary data subject to nonignorable missing data.
    Albert PS
    Biometrics; 2000 Jun; 56(2):602-8. PubMed ID: 10877323
    [TBL] [Abstract][Full Text] [Related]  

  • 19. A latent autoregressive model for longitudinal binary data subject to informative missingness.
    Albert PS; Follmann DA; Wang SA; Suh EB
    Biometrics; 2002 Sep; 58(3):631-42. PubMed ID: 12229998
    [TBL] [Abstract][Full Text] [Related]  

  • 20.
    ; ; . PubMed ID:
    [No Abstract]   [Full Text] [Related]  

    [Next]    [New Search]
    of 2.